Hover support show multiple column

[eromoe]

I didn't found a way to do this .

As I saw, plotly only support show 3 column when hovering, and 2 of them must be x and y . The example is

import plotly.express as px

gapminder = px.data.gapminder().query("year==2007 and continent=='Americas'")

fig = px.scatter(gapminder, x="gdpPercap", y="lifeExp", text="country", log_x=True, size_max=60)

fig.update_traces(textposition='top center')

fig.update_layout(
    height=800,
    title_text='GDP and Life Expectancy (Americas, 2007)'
)

fig.show()

But how do I make it show 6 column while hovering ??

In bokeh I can use tooltips to do this, example :

p = figure(title=title,
           x_range=x_range, y_range=y_range,
           x_axis_location="above",   plot_width=width, plot_height=len(y_range)*20,
           tools=TOOLS, toolbar_location='below',
           tooltips=[('name','@product_name'),('code', '@product_code'), ('date', '@date'), ('sc', '@sale_count'), ('pc', '@pred_count'), ('acc', '@acc%')])

p.rect(x=xcol, y=ycol, width=1, height=1,
   source=df,
   fill_color={'field': 'acc', 'transform': mapper},
   line_color=None)

At this point , bokeh is much more better than plotly .

[nicolaskruchten]

You can use the hover_data keyword argument of px.scatter() (or any px.function()) which accepts a list of column names and they are all displayed. Here's an example: https://plot.ly/python/hover-text-and-formatting/

[eromoe]

Because this does't work, the hover is missing when I use px.function 4 column in hover_data.
It only work with one.

My code is very simple , p2 is hourly timeseries with 1600 rows. there may be nan in ['price_plan_market', 'price_plan_store', 'price_flashsale', 'price_guide'] .

fig = px.bar(p2, x="ds", y="sale_count", 
                 hover_name="ds", hover_data=['price_plan_market', 'price_plan_store', 'price_flashsale', 'price_guide'])

fig.update_layout(
    width=800,
    height=400,
)

fig.show()

I found only when change to hover_data=['price_plan_market'] , it would show the hover info in which price_plan_market is not nan.

[nicolaskruchten]

Can you share more about what doesn’t work? I’m afraid I don’t understand. Maybe a code sample I could run to reproduce the problem would help...

[eromoe]

I use red point to indicate cursor since screen capture couldn't capture it .

This x position, price_plan_market is not nan, hover shows

This x position, price_plan_market is nan , hove doesn't show

[eromoe]

Above is single column situation .

It just showed nothing when use 4 column , looks like if there is a nan value in ['price_plan_market', 'price_plan_store', 'price_flashsale', 'price_guide'] then wouldn't show hover .
This is the test csv 1.txt

p2 = pd.read_csv('1.txt')
fig = px.bar(p2, x="ds", y="sale_count", 
                 hover_name="ds", hover_data=['price_plan_market', 'price_plan_store', 'price_flashsale', 'price_guide'])

fig.update_layout(
    width=800,
    height=400,
)

fig.show()

[nicolaskruchten]

Ah, thanks for the explanation. This does seem like a bug, and I will look into it!

[ShubhmAsati]

This method seems to working fine for showing multiple columns.. Add list of columns in hover_data and use customdata to show the column value in update traces hover template.

fig = px.pie(holdings, values='CurrentCashAmt', names='Ticker', title='Holdings',hover_name='Ticker',hover_data=["Ticker","P/L", "LTP", "AvgPrice", "Qty"])
fig.update_traces(textposition='inside', textinfo='percent+label',hovertemplate='Ticker: %{customdata[0][0]}<br> P/L %{customdata[0][1]}<br> LTP %{customdata[0][2]} <br> Buy Price %{customdata[0][3]} <br> Qty %{customdata[0][4]} ')

[patilabhay679]

have you tried converting nan to 0

[gvwilson]

Hi - we are currently trying to tidy up Plotly's public repositories to help us focus our efforts on things that will help users most. Since this issue has been sitting for several years, I'm going to close it. If it's still a concern, we'd be grateful if you could open a new issue (with a short reproducible example if appropriate) so that we can add it to our backlog. Thanks for your help - @gvwilson